一种适用于行星表面特征提取的实时SIFT算法

在行星探测任务中,针对尺度不变特征变换(SIFT)算法计算量大,无法同时满足对导航算法准确性和实时性要求的问题,提出了一种基于快速高斯模糊的并行化SIFT算法,即FG-SIFT算法.首先,将算法中构建高斯金字塔的二维高斯核函数分离成两个一维高斯函数,降低算法的计算复杂度.然后,对于每一维高斯函数,使用两个无限脉冲响应滤...

A Real-Time SIFT Algorithm for Planetary Surface Feature Extraction

In order to solve the problem that the scale invariant feature transform(SIFT)has a large amount of calculation and cannot meet the requirements of accuracy and real-time in the navigation algorithm,a parallel SIFT algorithm FG-SIFT based on fast Gaussian blur is proposed.First,the two-dimensional Gaussian kernel function,which constructs the Gaussian pyramid,is separated into two one-dimensional Gaussian functions to reduce the computational complexity.Then,two infinite impulse response filters are used in series to approximate each one-dimensional Gaussian kernel function to further reduce the computational complexity.Finally,using the advantage of parallel processing,the parallel computing scheme of each part of the algorithm is designed.Simulation results show that the computational efficiency of FG-SIFT algorithm is 15 times higher than that of the original SIFT algorithm,and the running efficiency of FG-SIFT algorithm on graphics processing unit is nearly 2 times higher than that of SIFT without fast Gaussian blur.This algorithm greatly reduces the calculation time of feature point extraction and improves the real-time performance.